Top AWS Jobs in Toronto

Build and operate MedMe’s AWS platform, including infrastructure, deployment pipelines, observability, audit logging, and security controls. Lead platform initiatives, consolidate CDK configurations, improve deployment workflows, support engineering teams, and guide infrastructure security and compliance. The role requires strong Terraform expertise, hands-on AWS CDK experience, production infrastructure ownership, and on-call experience. It is hybrid in Toronto with occasional travel.

Build and scale backend systems for Lyft’s Recommendations team, including pipelines and services that use rider context and signals to surface relevant offers. Responsibilities include system design, coding, code reviews, on-call support, project delivery, engineering best practices, mentoring, and promoting AI-assisted development. The role requires Python and Go, cloud platforms, distributed systems, databases, and strong collaboration skills, with bonus experience in ML serving, recommendation systems, feature stores, or experimentation.

Lead and mentor engineering teams to design, architect, and deliver scalable, maintainable software. Drive cross-team initiatives, partner with Product and Design, participate in code reviews, promote engineering best practices, and spend time on Staff Dev Projects to reduce technical debt and explore emerging technologies.

Hands-on senior backend engineer role building and maintaining Python/Django services. Design, implement, test, deploy, and support backend features, optimize performance, debug across systems, work with large datasets, REST APIs, background jobs, and PostgreSQL. Collaborate with Product and Engineering and own features end-to-end.

Build, maintain and scale the e-commerce front end across desktop and mobile. Collaborate with design, marketing, and ops to deliver features from concept to launch, own technical infrastructure, ensure high-quality UX and customer satisfaction, and support A/B testing and DevOps workflows.

As a Research Machine Learning Scientist, you will develop and apply deep learning techniques on large-scale datasets while collaborating with engineers. You will also research and innovate in AI applications to improve banking services.

Design and build end-to-end features using Python and C++; architect scalable distributed systems and performant SQL schemas; implement Docker and Kubernetes workflows on AWS; design data environments and optimize queries; integrate AI agentic tools to automate development; collaborate with cloud infrastructure to maintain resilient, cloud-native applications.

Develop and scale state-of-the-art computer vision pipelines for aerial and oblique imagery. Train and improve segmentation, detection, and generative models, run large-scale PyTorch experiments, maintain modular ML infrastructure, and collaborate on deployment and inference optimizations while reproducing top-tier research.

Drive Cohere's AWS-sourced and AWS-influenced partner pipeline. Define and execute partner GTM for the Enterprise Market; recruit, onboard, enable and certify partners; lead co-selling, joint pipeline generation, business planning and QBRs; relay partner feedback to product and policy teams and evangelize Cohere at events.

Work directly with strategic customers to design, build, deploy, and operate production AI and data systems on Shakudo. Responsibilities include discovery, architecture, data pipelines, RAG/agent workflows, Kubernetes/cloud deployments, production support, governance, and driving adoption and measurable business outcomes.

The role involves collaboration with teams to develop solutions, maintain quality standards, and provide technical support, focusing on full-stack development using a variety of technologies.

Join Paidiem's talent community for future opportunities in various roles including development, product management, customer success, and more.

The Full Stack Intermediate Software Developer will work on critical platform projects, focusing on product development, solution architecture, and coding best practices while collaborating with the team and ensuring application security.

Leads Wattpad’s Platform Engineering team, overseeing backend platforms supporting social, notifications, subscriptions, and coin economy features. Responsibilities include managing and mentoring engineers, setting technical direction and roadmaps, guiding architecture and code quality, coordinating project resources, collaborating with Product and business stakeholders, supporting hiring, and managing team performance and development. The role requires significant backend distributed-systems expertise and hands-on experience with APIs, application design, Unix platforms, and compiled programming languages.

Design, build, and operate Rust services powering Scribd’s large-scale Content Library and core infrastructure. Own features end to end, evolve Python tooling, optimize DataFusion, Parquet, S3, caching, and PostgreSQL/Aurora systems, and strengthen governance through lineage, authorization, and deletion controls. Lead cross-functional technical projects, support platform users, mentor engineers, improve developer workflows, and maintain production reliability through observability, on-call, and incident response.

Designs and maintains scalable test automation frameworks using Java, Python, and Playwright. Performs functional, API, integration, database, migration, performance, security, and accessibility testing. Validates Snowflake data, ETL processes, transactions, and business rules with complex SQL. Integrates tests into CI/CD pipelines and uses generative AI tools to improve testing productivity and coverage. Establishes AI testing governance, analyzes defects, mentors junior engineers, and drives quality engineering improvements.

Define and evolve Interac’s enterprise data architecture strategy, target-state blueprints, transition roadmaps, governance standards, and reference architectures. Establish guardrails for data quality, lineage, metadata, ownership, access, retention, privacy, security, and regulatory compliance. Lead architecture reviews and risk assessments across warehouse and lakehouse environments, while guiding scalable integration, semantic modeling, data products, and analytics and AI enablement across cloud, SaaS, and on-premises platforms.

Leads architecture and hands-on development of scalable, cloud-native full-stack applications using Java, Spring Boot, GCP, microservices, and big data technologies. Manages cross-functional engineering teams, mentors staff, establishes technical standards, and oversees secure software development, reliability KPIs, documentation, releases, and cloud optimization. Develops APIs, prototypes solutions, supports infrastructure-as-code, and collaborates with product, architecture, SRE, and business stakeholders.

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.

Build and own ML infrastructure for distributed training, inference, experiment tracking, model registries, and CI/CD. Enable active-learning and closed-loop optimization, collaborate with computational scientists, and mentor colleagues to translate research prototypes to production-grade systems.

Senior client-facing Sales Engineer for IIoT platform sales in manufacturing. Perform technical discovery, design custom solutions and demos, run pilots, support RFIs/RFPs, liaise with product teams, assist resellers, and attend customer meetings and conferences to translate factory-floor challenges into Litmus platform value.

Work with prospects and customers to design, configure, and implement Litmus Edge and Litmus Edge Manager in proofs-of-concept and production. Lead implementations, provide L3/L4 support, create best-practice content, assist sales with technical proposals, and deliver partner and customer-facing demos and training.

Design, build, and scale resilient distributed payment systems handling 1,000+ transactions per second. Collaborate with Product, Revenue Operations, Cloud Platform, and Security teams to shape product requirements and roadmaps. Lead AI-augmented software delivery, code reviews, testing, observability, performance optimization, incident response, on-call rotations, and root cause analysis while maintaining strict security, reliability, and low-latency standards.

Lead design and delivery of reliability projects for Coinbase's platform: secure service configuration and secrets management, improve canary-based deployments, partner with core services to increase scalability and reduce incidents, drive reliability best practices, and participate in on-call rotations.

Lead end-to-end AI-first transformation for operations: define problems, design architecture, build agentic systems and automation pipelines, integrate with CRMs and operational tooling, ship production solutions and drive company-wide AI adoption.